The invention relates to a method for detection and/or tracking of objects in motion in a scene under surveillance, in which besides the objects in motion, interfering objects and/or interfering regions—hereinafter called interfering factors—can occur, in which the scene under surveillance, a plurality of regions are defined that are divided up into various region classes; a first region class includes sensitive regions, in which no and/or only insignificant interfering factors are located and/or are to be expected; and for detection and/or tracking of the objects in motion in the sensitive regions, a sensitive content analysis is performed. The invention also relates to an apparatus, which is embodied for performing the aforementioned method, and to a corresponding computer program.
Video surveillance systems typically include a plurality of surveillance cameras and are used for monitoring public or commercial areas. Examples of such video surveillance systems can be found in railroad stations, airports, factories, schools, universities, prisons, hospitals, and so forth. Often, the image data streams furnished by the surveillance cameras are no longer manually watched by surveillance personnel; instead, algorithms for content analysis of the image data streams are employed, so as to detect relevant incidents automatically and trip alarms as needed. Compared to the use of surveillance personnel, this automated procedure has the advantage of considerable savings on labor costs, and furthermore, the surveillance is independent of the current state (fatigue, and so forth) of the observer.
For automatic evaluation of the image data streams, it is a widely employed principle to separate objects in motion from the (essentially static) scene background (this is known as object segmentation), to track them over time (known as tracking), and to trip an alarm if relevant motions occur. Often, the image distinctions between a current camera image and a so-called scene reference image which models the static scene background are evaluated for the object segmentation.
Such video surveillance systems and automatic evaluations are known for instance from published German Patent Application DE 199 32 662 A1 or published German Patent Application DE 102 10 926 A1, which form the general prior art.